Artificial intelligence for knowing the anticipation of client from online food delivery using big data

Big data analytics carried out with various methods in a systematic way to identify the data variables performances and in this arena the data has many ways to get separate from each other, this type of analysis are applicable to organize data files that are extremely large or composite to be structured by regular analytical tools. The innovative stage of recent technologies influences the strategic practices of an organization for competitive scenario. The amount of data is growing in a fast phase throughout the various sections of business operations. Likewise, the swift of big data is noticed with the online food delivery units. This paper is comprised with explicit information through a detailed research on identifying the tools which assist in knowing online food delivery expectation from their clients, as the flexibly of food industry is confounded, in light of different guidelines with the varied interest on ordering food; in this way, the perceivability of user for time consumption on receiving their food order, apparently saving their cash based on budget over comparison with similar items. Nevertheless, food delivery vendors can't utilize all the assembled data and are not using the potential that is conceivable. Thus the primary objective of this big data analysis is to obtain an effective and efficient classification of data for knowing the anticipation of users from online food delivery applications. Furthermore on knowing the tools and methods that are suitable for analyzing big data.